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Cluster Analysis: Basic Concepts and Algorithms - Case Study Example
Cluster Analysis: Basic Concepts and Algorithms Case Study
Published on May 8, by Shona McCombes. Revised on June 19, A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research. A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating and understanding different aspects of a research problem. Table of contents When to do a case study Select a case Build a theoretical framework Collect your data Describe and analyze the case.
What is cluster analysis? When should you use it for your survey results?
Cluster analysis is a statistical method used to group similar objects into respective categories. It can also be referred to as segmentation analysis, taxonomy analysis, or clustering. The goal of performing a cluster analysis is to sort different objects or data points into groups in a manner that the degree of association between two objects is high if they belong to the same group, and low if they belong to different groups. Instead, cluster analysis is leveraged mostly to discover structures in data without providing an explanation or interpretation.
The input is a sequence of pairs of integers, where each integer represents an object of some type and we are to interpret the pair p q as meaning p is connected to q. We assume that "is connected to" is an equivalence relation : symmetric : If p is connected to q , then q is connected to p. An equivalence relation partitions the objects into equivalence classes or connected components.